Applying Genetic Algorithm in a Multi-Objective Design Process Optimization Problem

• Main Author: Celine Kurniajaya
• Other Authors: Chao Ou-Yang
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/92awxc

碩士 === 國立臺灣科技大學 === 工業管理系 === 106 === Design process scheduling is conducted by worker allocation to several tasks in project to achieve two objectives, minimizing the time delay penalty and minimizing total working cost. By minimizing these, the company can provide cheaper product. It can also make product launching faster. Thus, the company will have a competitive advantage. Because there were two objectives that need to reach, this study used Multi-Objective Genetic Algorithm and pareto-optimality principle to solve multi-objective problem in a wheels’ design process in a Taiwanese UAV company. The solutions for this problem was called pareto-optimal solutions. From MOGA, we got the minimum time delay penalty, minimum working cost, and the combination of which worker finishes the task. Time differences was the differences between expected working time and actual completion time. This research’s goal is to provide pareto-optimal solutions that will be given to management for decision making. It is also expected to show the possible minimum working hours and additional hours to finish tasks in a wheels’ design process.